CN110782351A - Data processing method, system, device and storage medium suitable for daily end transaction - Google Patents
Data processing method, system, device and storage medium suitable for daily end transaction Download PDFInfo
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- CN110782351A CN110782351A CN201911042149.5A CN201911042149A CN110782351A CN 110782351 A CN110782351 A CN 110782351A CN 201911042149 A CN201911042149 A CN 201911042149A CN 110782351 A CN110782351 A CN 110782351A
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
- G06F16/2282—Tablespace storage structures; Management thereof
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/03—Credit; Loans; Processing thereof
Abstract
The invention discloses a data processing method, a system, a device and a storage medium suitable for daily end transaction, wherein the data processing method comprises the following steps: obtaining identification information of transaction data stored in a database, wherein the identification information comprises a service channel identification and a borrow ID; splitting the database into a plurality of sub-databases according to different identification information; and executing daily end transaction processing in parallel based on the plurality of sub-databases respectively. By adopting the technical scheme of the invention, the single-base transaction data can be limited while the purity of the transaction data is ensured, so that the service capacity is greatly improved, the processing efficiency is improved, and the accounting rules are unified.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a data processing method, system, device and storage medium suitable for end-of-day transactions.
Background
Most of assets of a consumption financial company are obtained by docking an asset loan-aid channel, an accounting result is subject to an accounting system of other parties, compared with an original bank credit system, the daily and final transaction processing data volume is large, the processing time is seriously too long (for example, more than 10 hours) when the borrowing scale reaches more than ten million levels, the accounting logic of interest improvement and the like is different from the accounting rule of self-accounting products, the uniform accounting processing is difficult to realize, and the data change of interest improvement and the like is difficult to track.
At present, the commonly used data processing method is as follows:
and directly storing the other party daily and final accounting result list application program into a list database list table, and respectively covering the previous data processing results with borrowing data, repayment plan, daily and final accounting data and the like. According to the method, data are not required to be processed, the data which are subjected to accounting by the other system are directly used for covering the data of the previous day, the processing efficiency is guaranteed, the unification of accounting rules cannot be realized, and the correctness of the data is difficult to guarantee.
And carrying out daily final data accounting on each piece of borrow again, and storing the borrowed borrow into the database after the accounting is finished. The method re-accounts the data which is accounted by the other party system and then records the data into the database, and although the problem of unified accounting rules can be solved, the method has poor processing performance and long time consumption and cannot meet the requirement of batch time at the end of day.
Disclosure of Invention
In order to solve the above problems in the prior art, the present invention provides a data processing method, system, device and storage medium suitable for daily and final transaction, which realizes the unification of accounting rules while ensuring the processing efficiency.
According to an aspect of the present invention, an embodiment of the present invention provides a data processing method suitable for end-of-day transactions, which includes: obtaining identification information of transaction data stored in a database, wherein the identification information comprises a service channel identification and a borrow ID; splitting the database into a plurality of sub-databases according to different identification information; and executing daily end transaction processing in parallel based on the plurality of sub-databases respectively.
In some embodiments of the present invention, splitting the database into a plurality of sub-databases according to the different identification information comprises: and splitting the database into a plurality of sub-databases according to different service channel identifications, wherein the service channel identifications of the transaction data in any one of the sub-databases are consistent with each other.
In some embodiments of the present invention, splitting the database into a plurality of sub-databases according to different identification information further comprises: judging whether the data volume of the transaction data corresponding to the service channel identification exceeds a threshold value; if so, splitting the sub-database corresponding to the service channel identification into a plurality of data tables according to the borrow ID, wherein the borrow IDs of the transaction data in any one of the data tables are consistent with each other.
In some embodiments of the present invention, splitting the database into a plurality of sub-databases according to different identification information further comprises: if not, the sub-database is regarded as a data table.
In some embodiments of the invention, performing end-of-day transaction processing based on the plurality of sub-databases in parallel, respectively, comprises: initiating N fragmentation tasks, wherein N is a positive integer multiple of the number of data tables; acquiring a plurality of pieces of transaction data from a data table according to the task number of the slicing task; extracting transaction elements of the plurality of pieces of transaction data, wherein the transaction elements include: repayment plan information, repayment mode information, repayment interest rate information, interest counting record information and joint loan parameter information; processing the plurality of pieces of transaction data in parallel based on the transaction elements.
In some embodiments of the invention, the data processing method further comprises: and storing the processing result in a buffer queue.
According to another aspect of the present invention, an embodiment of the present invention provides a data processing system suitable for end-of-day transactions, comprising:
the system comprises an identification acquisition module, a data processing module and a data processing module, wherein the identification acquisition module is used for acquiring identification information of transaction data stored in a database, and the identification information comprises a service channel identification and a borrow ID;
the splitting module is used for splitting the database into a plurality of sub databases according to different identification information;
and the processing module is used for respectively executing daily and final transaction processing in parallel based on the plurality of sub-databases.
In some embodiments of the present invention, splitting the database into a plurality of sub-databases according to the identification information comprises: and splitting the database into a plurality of sub-databases according to different service channel identifications, wherein the service channel identifications of the transaction data in any one of the sub-databases are consistent with each other.
In some embodiments of the present invention, splitting the database into a plurality of sub-databases according to different identification information further comprises: judging whether the data volume of the transaction data corresponding to the service channel identification exceeds a threshold value; if so, splitting the sub-database corresponding to the service channel identification into a plurality of data tables according to the borrow ID, wherein the borrow IDs of the transaction data in any one of the data tables are consistent with each other.
In some embodiments of the present invention, splitting the database into a plurality of sub-databases according to different identification information further comprises: if not, the sub-database is regarded as a data table.
In some embodiments of the invention, performing end-of-day transaction processing based on the plurality of sub-databases in parallel, respectively, comprises: initiating N fragmentation tasks, wherein N is a positive integer multiple of the number of data tables; acquiring a plurality of pieces of transaction data from a data table according to the task number of the slicing task; extracting transaction elements of the plurality of pieces of transaction data, wherein the transaction elements include: repayment plan information, repayment mode information, repayment interest rate information, interest counting record information and joint loan parameter information; processing the plurality of pieces of transaction data in parallel based on the transaction elements.
In some embodiments of the invention, the data processing system further comprises: and the storage module is used for storing the processing result in the cache queue.
According to a further aspect of the invention, embodiments of the invention provide a data processing apparatus adapted for end-of-day transactions, comprising a memory for storing one or more computer instructions and a processor; the processor is configured to invoke and execute the one or more computer instructions to implement the data processing method of any of the preceding.
According to yet another aspect of the present invention, an embodiment of the present invention further provides a computer storage medium storing one or more computer programs that, when executed, implement the data processing method of any one of the preceding claims.
According to the embodiments of the invention, the single-base transaction data can be limited while ensuring the purity of the transaction data, so that the service capacity is greatly improved. Meanwhile, the data processing efficiency is improved, and the unification of the accounting rules can be realized while the processing efficiency is ensured. In addition, the embodiment of the invention increases the IO pressure of the database in a multi-item processing parallel mode, and can greatly improve the effectiveness of the IO of the database by adopting a batch read-write mode, thereby further improving the processing efficiency.
Drawings
In order to facilitate understanding of the present invention, the present invention will be described in detail with reference to the following embodiments in conjunction with the accompanying drawings.
FIG. 1 is a schematic flow chart diagram of a data processing method suitable for end-of-day transactions, according to an embodiment of the invention;
FIG. 2 is a schematic flow chart illustrating the database splitting process of FIG. 1 into a plurality of sub-databases according to different identification information;
FIG. 3 is another schematic flow chart of the database splitting process of FIG. 1 into a plurality of sub-databases according to different identification information;
FIG. 4 is a schematic flow chart illustrating the end-of-day transaction process of FIG. 1 based on a plurality of sub-databases;
FIG. 5 is a block diagram of a data processing system suitable for end-of-day transactions, according to an embodiment of the present invention;
FIG. 6 is a block diagram of another data processing system suitable for end-of-day transactions, according to an embodiment of the present invention.
Detailed Description
Various aspects of the invention are described in detail below with reference to the figures and the detailed description. Well-known modules, units and their interconnections, links, communications or operations with each other are not shown or described in detail. Furthermore, the described features, architectures, or functions can be combined in any manner in one or more implementations. It will be understood by those skilled in the art that the various embodiments described below are illustrative only and are not intended to limit the scope of the present invention. It will also be readily understood that the modules or units or processes of the embodiments described herein and illustrated in the figures can be combined and designed in a wide variety of different configurations.
Fig. 1 is a flow diagram of a data processing method suitable for end-of-day transactions according to an embodiment of the present invention, which, in an embodiment of the present invention and referring to fig. 1, may include the following processes or steps:
100: obtaining identification information of transaction data stored in a database;
in an embodiment of the present invention, the identification information of the transaction data may include a service channel identification and a borrow ID;
110: splitting the database into a plurality of sub-databases according to different identification information;
120: and executing daily transaction processing in parallel based on the plurality of sub-databases respectively.
Optionally, in this embodiment, the process 110 may be implemented as follows:
and splitting the database into a plurality of sub databases according to different service channel identifiers.
In the embodiment of the invention, the service channel identifications of the transaction data in any one of the sub-databases are consistent with each other.
Because the traffic of each service channel is different, for some service channels with larger traffic, the performance capacity of single data still cannot support the data processing of the daily end transaction. In this regard, embodiments of the present invention provide the following execution flow:
fig. 2 is a flow chart of the process 110 of fig. 1, and referring to fig. 2, the process 110 further includes:
111: splitting the database into a plurality of sub databases according to different service channel identifiers;
112: judging whether the data volume of the transaction data corresponding to the service channel identification exceeds a threshold value;
113: if the data is judged to be yes, the sub-database corresponding to the service channel identification is divided into a plurality of data tables according to the borrow ID.
In an embodiment of the present invention, the debit IDs of the transaction data in any one of the plurality of data tables are identical to each other.
In the implementation mode of the invention, the business channel identification and the borrow ID are adopted to carry out the library division according to the double rules, so that the data in the same channel are relatively centralized, thereby ensuring that the data capacity of a single library is not overlarge, simultaneously, the participation of the borrow ID also ensures that the data are dispersed in different tables in a proper scale, and ensuring that the response performance efficiency of the database is high enough when the transaction is processed. Based on the method, the single-base transaction data is limited while the purity of the transaction data is ensured, so that the service capacity is greatly improved.
In addition, in the embodiment of the invention, the sub-databases are divided by borrowing the ID, so that the data in the data table can reach a certain scale again, and the current data table is divided again when the performance capacity of single data cannot support the data processing of the end-of-day transaction. For example, the borrow ID is data with a time series nature, and thus, can be split again by time segments. Therefore, the purpose of naturally segmenting data without involving the original database data migration is achieved.
For some traffic channels with small traffic volume, the performance capacity of single data is enough to support the data processing of the daily end transaction. In this regard, embodiments of the present invention provide the following execution flow:
fig. 3 is another flow diagram of the process 110 of fig. 1, and referring to fig. 3, the process 110 further includes:
114: if not, the sub-database is regarded as a data table.
Meanwhile, in order to improve processing efficiency, referring to fig. 4, in an embodiment of the present invention, the process 120 includes:
121: initiating N fragmentation tasks;
122: acquiring a plurality of pieces of transaction data from a data table according to the task number of the fragmentation task;
123: extracting transaction elements of a plurality of pieces of transaction data;
124: processing the plurality of pieces of transaction data in parallel based on the transaction elements.
In the embodiment of the present invention, the number N of the fragmentation tasks is a positive integer multiple of the number of the data tables, for example: when the number of the data tables is 16, N is 16, 32 or 64. Therefore, the service data corresponding to each fragmentation task can be ensured to come from the same data table.
In an embodiment of the present invention, the task number of the fragmentation task is determined by the fragmentation rule, and in an alternative embodiment, the number of pieces of acquired transaction data may be determined by the task number. For example, the task number may be obtained by modulo the sub-table number by the data ID, with the result corresponding to the number of pieces of transaction data acquired by the slicing task. Therefore, the optimal processing number executed by each slicing task can be obtained, and the processing performance is improved.
In an embodiment of the present invention, the transaction elements may include payment plan information, payment method information, payment interest rate information, interest record information, joint loan parameter information, and the like.
After the corresponding transaction elements are obtained, a plurality of transaction data can be distributed to a plurality of threads for parallel processing, and no database access exists in the calculation processing process. Therefore, the reprocessing of the daily and final transaction data is realized, and the accounting rules are unified.
Finally, in an embodiment of the present invention, the data processing method may further include: and storing the processing result in a buffer queue.
Optionally, after the current fragmentation task is executed, the processed multiple pieces of transaction data are taken out from the buffer queue, and the results are stored in the database according to different data types.
Based on the above, according to the embodiments of the present invention, the transaction data of the single base can be limited while ensuring the purity of the transaction data, so that the service capacity is greatly increased. Meanwhile, the data processing efficiency is improved, and the unification of the accounting rules can be realized while the processing efficiency is ensured. In addition, the embodiment of the invention increases the IO pressure of the database in a multi-item processing parallel mode, and can greatly improve the effectiveness of the IO of the database and improve the application throughput to the maximum extent by adopting a batch read-write mode, thereby further improving the processing efficiency.
Fig. 5 is a block diagram of a data processing system suitable for end-of-day transactions, which may be installed or loaded on a server, or a server including the data processing system, according to an embodiment of the present invention, and referring to fig. 5, the data processing system 1 includes:
the identification acquisition module 11 is configured to acquire identification information of the transaction data stored in the database, where the identification information includes a service channel identification and a borrow ID;
the splitting module 12 is configured to split the database into a plurality of sub-databases according to different identification information;
and the processing module 13 is configured to execute daily and final transaction processing in parallel based on the plurality of sub-databases.
In an embodiment of the present invention, the splitting module 12 may split the database into a plurality of sub-databases according to the identification information, including: and splitting the database into a plurality of sub-databases according to different service channel identifications, wherein the service channel identifications of the transaction data in any one of the sub-databases are consistent with each other.
In an embodiment of the present invention, the splitting module 12 may split the database into a plurality of sub-databases according to different identification information, and further include: judging whether the data volume of the transaction data corresponding to the service channel identification exceeds a threshold value; if the data is judged to be yes, the sub-database corresponding to the service channel identification is divided into a plurality of data tables according to the borrow ID, wherein the borrow IDs of the transaction data in any one of the data tables are consistent with each other.
In an optional embodiment, the splitting module 12 may split the database into a plurality of sub-databases according to different identification information, and further include: if not, the sub-database is regarded as a data table.
In an embodiment of the present invention, the executing, by the processing module 13, the end-of-day transaction processing based on the plurality of sub-databases respectively in parallel may include: initiating N fragmentation tasks, wherein N is a positive integer multiple of the number of data tables; acquiring a plurality of pieces of transaction data from a data table according to the task number of the fragmentation task; extracting transaction elements of a plurality of pieces of transaction data, wherein the transaction elements include: repayment plan information, repayment mode information, repayment interest rate information, interest counting record information and joint loan parameter information; a plurality of pieces of transaction data are processed in parallel based on the transaction elements.
Fig. 6 is a block diagram of another data processing system 1 suitable for end-of-day transactions according to an embodiment of the present invention, and referring to fig. 6, in the embodiment of the present invention, the data processing system 1 further includes: and the storage module 14 is used for storing the processing result in the buffer queue.
Optionally, the embodiment of the present invention provides a data processing apparatus suitable for end-of-day transactions, for example, a server, and the process control apparatus includes a memory for storing one or more computer instructions; and the processor is used for calling and executing the one or more computer instructions so as to realize the data processing method suitable for the end-of-day transaction provided by the previous embodiment or implementation mode of the invention. Optionally, in an implementation manner of the embodiment of the present invention, the data processing apparatus for end-of-day transactions may further include an input/output interface for data communication. For example, the process control device may be a computer, an intelligent terminal, a server, or the like.
Embodiments of the present invention also provide a computer storage medium storing one or more computer instructions for implementing, when executed, the data processing method suitable for end-of-day transactions provided by the foregoing embodiments or implementations of the present invention. For example, the storage medium may include a hard disk, a floppy disk, an optical disk, and the like.
Although some embodiments have been described herein by way of example, various modifications may be made to these embodiments without departing from the spirit of the invention, and all such modifications are intended to be included within the scope of the invention as defined in the following claims.
The particular embodiments disclosed herein are illustrative only and should not be taken as limitations upon the scope of the invention, which is to be accorded the full scope consistent with the claims, as defined in the appended claims. Accordingly, the particular illustrative embodiments disclosed above are susceptible to various substitutions, combinations or modifications, all of which are within the scope of the disclosure. The data processing methods, systems, devices, and storage media illustratively disclosed herein as being suitable for end-of-day transactions may suitably be practiced in the absence of any element not specifically disclosed herein or in the absence of any optional component disclosed herein. All numbers and ranges disclosed above may also vary somewhat. Whenever a numerical range with a lower limit and an upper limit is disclosed, any number and any included range falling within the range is specifically disclosed. In particular, any range of values disclosed herein is to be understood as being inclusive of any of the values and ranges encompassed within the broader range of values. Also, the terms in the claims have their plain, ordinary meaning unless otherwise explicitly and clearly defined by the applicant.
Through the above description of the embodiments, those skilled in the art will clearly understand that the present invention can be implemented by combining software and a hardware platform. With this understanding in mind, all or part of the technical solutions of the present invention that contribute to the background can be embodied in the form of a software product, which can be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, etc., and includes instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods according to the embodiments or some parts of the embodiments.
In addition, the number of components in the claims includes one or at least one unless otherwise specified. To the extent that a term or phrase is intended to have a meaning or meaning other than that understood in the specification, it is intended to be open ended in that the term or phrase is intended to be more pronounced than as specifically defined in the specification.
Claims (14)
1. A data processing method suitable for end-of-day transactions, the data processing method comprising:
obtaining identification information of transaction data stored in a database, wherein the identification information comprises a service channel identification and a borrow ID;
splitting the database into a plurality of sub-databases according to different identification information;
and executing daily end transaction processing in parallel based on the plurality of sub-databases respectively.
2. The data processing method of claim 1, wherein splitting the database into a plurality of sub-databases according to the different identification information comprises:
and splitting the database into a plurality of sub-databases according to different service channel identifications, wherein the service channel identifications of the transaction data in any one of the sub-databases are consistent with each other.
3. The data processing method of claim 2, wherein splitting the database into a plurality of sub-databases according to different identification information further comprises:
judging whether the data volume of the transaction data corresponding to the service channel identification exceeds a threshold value;
if so, splitting the sub-database corresponding to the service channel identification into a plurality of data tables according to the borrow ID, wherein the borrow IDs of the transaction data in any one of the data tables are consistent with each other.
4. The data processing method of claim 3, wherein splitting the database into a plurality of sub-databases based on different identification information further comprises:
if not, the sub-database is regarded as a data table.
5. The data processing method of claim 3 or 4, wherein performing end-of-day transaction processing based on the plurality of sub-databases respectively in parallel comprises:
initiating N fragmentation tasks, wherein N is a positive integer multiple of the number of data tables;
acquiring a plurality of pieces of transaction data from a data table according to the task number of the slicing task;
extracting transaction elements of the plurality of pieces of transaction data, wherein the transaction elements include: repayment plan information, repayment mode information, repayment interest rate information, interest counting record information and joint loan parameter information;
processing the plurality of pieces of transaction data in parallel based on the transaction elements.
6. The data processing method of claim 1, wherein the data processing method further comprises:
and storing the processing result in a buffer queue.
7. A data processing system adapted for end-of-day transactions, the data processing system comprising:
the system comprises an identification acquisition module, a data processing module and a data processing module, wherein the identification acquisition module is used for acquiring identification information of transaction data stored in a database, and the identification information comprises a service channel identification and a borrow ID;
the splitting module is used for splitting the database into a plurality of sub databases according to different identification information;
and the processing module is used for respectively executing daily and final transaction processing in parallel based on the plurality of sub-databases.
8. The data processing system of claim 7, wherein splitting the database into a plurality of sub-databases based on different ones of the identification information comprises:
and splitting the database into a plurality of sub-databases according to different service channel identifications, wherein the service channel identifications of the transaction data in any one of the sub-databases are consistent with each other.
9. The data processing system of claim 8, wherein splitting the database into a plurality of sub-databases based on different ones of the identification information further comprises:
judging whether the data volume of the transaction data corresponding to the service channel identification exceeds a threshold value;
if so, splitting the sub-database corresponding to the service channel identification into a plurality of data tables according to the borrow ID, wherein the borrow IDs of the transaction data in any one of the data tables are consistent with each other.
10. The data processing system of claim 9, wherein splitting the database into a plurality of sub-databases based on different ones of the identification information further comprises:
if not, the sub-database is regarded as a data table.
11. The data processing system of claim 9 or 10, wherein performing end-of-day transaction processing based on the plurality of sub-databases in parallel, respectively, comprises:
initiating N fragmentation tasks, wherein N is a positive integer multiple of the number of data tables;
acquiring a plurality of pieces of transaction data from a data table according to the task number of the slicing task;
extracting transaction elements of the plurality of pieces of transaction data, wherein the transaction elements include: repayment plan information, repayment mode information, repayment interest rate information, interest counting record information and joint loan parameter information;
processing the plurality of pieces of transaction data in parallel based on the transaction elements.
12. The data processing system of claim 7, wherein the data processing system further comprises:
and the storage module is used for storing the processing result in the cache queue.
13. A data processing device suitable for end-of-day transactions, comprising a memory and a processor,
the memory is to store one or more computer instructions;
the processor is configured to invoke and execute the one or more computer instructions to implement the method of any of claims 1-6.
14. A computer storage medium storing one or more computer programs, wherein the one or more computer programs, when executed, implement the method of any of claims 1-6.
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